PUTTING THE PIECES TOGETHER

DYNAMIC MODELLING OF RIVER RESTORATION

MEASURES

Samantha Jane Hughes1-2, Mario Santos1, Rui Cortes2, João Cabral1,

Chris Gardner3, Bella Davies3

1.Applied Ecology Laboratory, Centre for Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal.

2. Fluvial Ecology Laboratory, Centre for Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal.

3. South East Rivers Trust, Denmark Road, Carshalton, Surrey SM5 2JG, United Kingdom

In a nutshell…

• Altered systems• Different impacts across different scales

• River restoration• Different measures across different scales

• Links across different networks

• The role of dynamic predictive modelling• Stochastic Dynamic Methodology

• Concept – method - application

• A conceptual model for river restoration• Case study challenge

Altered river systems• Impacts of human activity

• Across spatial and temporal scales

• Complex interactions in dynamic systems

• Losses• Ecosystem processes, structure and function

• System resilience• Stochastic events: flood, wildfire, storm events,

human disasters

• Ecosystem services

• Components of well-being• Governance - compliance

• WFD, Habitats, Flood

• Socio-economic impacts

• e.g. health

Uncertainty in dynamic systems

Decomposition of variance in macroinvertebrate relative abundance data 3 spatial scales (Odelouca River, Algave, Portugal)

Hughes, SJ, Ferreira MT Cortes RV (2008). Hierarchical spatial patterns and drivers of change in benthic macroinvertebrate communities in an intermitent Mediterranean river.Aquatic Conservation: marine and freshwater ecosystems 18: 742-760.

River restoration

Restoration objectives

The role of dynamic predictive modelling

• A tool for decision support and governance

• Able to embrace system complexity and stochasticity

• Use existing data bases

• Parameterisation using gradients in data

• Assess cause-effect relationships - relevant scenarios, including stochastic events

• Provide feedback to guide maintenance and inform future management

• WFD context: to prevent deterioration or improve ecological status

• Refine restoration measures

• What issues still exist?

• What can be done to address them?

• What could be done next?

• Demonstrate restoration benefits to inform future funding bids

• Dynamic temporal outputs – graphs, tables, values

• Visualisation – coupled with GIS

Stochastic Dynamic Methodology (StDM)• A sequential modelling method

• Comprises static and dynamic components

• Holistic principles

• Complex and dynamic processes that shape socio-ecological systems

• Linear / non-linear / cumulative

• Indicator response

• Modular

• Integrate different data sources / types

• Sensitivity analysis

• Assessment of uncertainty

• StDM model complexity determinants

• The problem

• Choice of the key-components in studied ecosystem

• Available data

• StDM + GIS = spatial projection of results

Stochastic Dynamic Methodology (StDM)

Assess explanatory and response variables

Obtain correlative output to populate the dynamic model

Data-base of explanatory and response variable values broad enough to capture a wider gradient of the pertinent scenarios

National River Restoration inventories

River Wiki

Rivers Trust projects

Funded projects

Grey literature

Statutory body data bases e.g. WFD

A conceptual model for river restoration

Restoration scenarios Stochastic events

A conceptual model for river restoration

• Demonstration → Project

• CITAB, RRC, SERT

• Based on a small selection of restoration

measures

• NRRI and project data

• LWD and deflectors

• Assess processes conditions leading to project

success

• Objectives

• Scenarios

Integrative Research in Environment, Agro-Chains and Technology

Bio-Economy and Sustainability